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Record W3034287813 · doi:10.2490/jjrmc.57.305

Orthopaedic Care for Cancer Locomotive Syndrome in Cancer Patients

2020· article· en· W3034287813 on OpenAlexaff
Hitomi Hara

Bibliographic record

VenueThe Japanese Journal of Rehabilitation Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsAssociation des Démographes du Québec
Fundersnot available
KeywordsCancerMedicineInternal medicine

Abstract

fetched live from OpenAlex

がん患者の運動器障害「がんロコモ」に対して整形外科医が積極的かつ包括的にかかわっていくことは,がん患者のADL,QOLの維持・向上を目的とし,がん患者が最期まで人間らしく生きることを支援することである.そのために,がん患者の運動器障害の原因を特定し,評価し,適切な治療を行う必要がある.がんの診断から終末期まで,がん患者の運動機能の低下を最小限にすることが整形外科医の役割である.骨転移を含めたがんロコモ対策にはチーム医療が必要である.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.335
Teacher spread0.317 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueThe Japanese Journal of Rehabilitation MedicineSame topicSpinal Fractures and Fixation TechniquesFrench-language works237,207